They are looking for a VP of Data Science & Analytics to join Snap Inc! In this role reporting to the VP of Product & Design, you will be responsible for leading an organizational effort toward better understanding user needs and pain points, and propose roles that data science can play to further this goal. Working from either Los Angeles or San Francisco, CA, you will build high performance, responsive teams of data scientists and analysts that are able to gather and synthesize data quickly and accurately.
- What you’ll do:
- Build high performance, responsive teams of data scientists, and analysts that are able to gather and synthesize data quickly and accurately
- Support an organizational effort toward better understanding user needs and pain points, and propose roles that data science can play to further this goal
- Support data-informed decision-making, throughout the Product Org and broader company
- Develop an investment strategy to define, grow and maintain an exemplary data science organization
- Constantly look for strategic ways to expand the charter of the Data Science team beyond causal inference, starting with Ranking Data Science, and Market-Place Dynamics
- Ensure data best practices and play a critical role in building the data-informed culture throughout Snap
- Be a thought leader and evangelist to drive adoption and knowledge at all levels of the organization
- Determine how to leverage data science, machine learning, and other analytical techniques to offer actionable insights both internally & externally
- Define and drive the strategy for investments, working closely with key business analytics leaders, and executive management
- Participate heavily with Snap’s executive team, help set business strategy, represent product data science, initiate and debate key strategic topics and opportunities from your team’s work, and drive bold high-impact decisions
- Collaborate with cross-functional partners in product, engineering, operations, finance, and marketing to define and build data-informed business strategy and roadmaps
- Partner with the data engineering team, technology architects and software developers to empower our lines of businesses with business intelligence
- Provide timely turnarounds on data requests for “one-off” activities, such as acquisition, partnership analyses, and new product initiatives
- Provide technical leadership were suitable to support colleagues throughout Snap
- Implement a leveling and performance management system for Data Science as a whole, across Snap
- Knowledge, Skills & Abilities:
- Have strong technical domain know-how to coach and grow the team
- Have a strong builder mentality, can bring order to chaos, and know how to effectively “bring people along”
- Bring positive influence on culture and value for Snap’s data practice
- Are able to effectively challenge the status quo and plan insightful roadmaps
- Experience in a complex, cross-functional organization where your teams need to collaborate and integrate with other teams across many disciplines
- Passionate to innovate solutions, delight users, and inspire colleagues
- Strong strategic business acumen, change management, and continuous improvement champion
- Mentor and coach team on career paths
- Strong interpersonal skills and ability to influence through creating fellowship
- Experience in data-oriented due diligence within the context of M&A transactions
- Excellent written and verbal communication skills
- Embody Snap’s values
- Minimum Qualifications:
- BS/BA degree or equivalent years of experience
- 10+ years’ experience in algorithmic engineering, data science, or machine learning
- 5+ years of experience in managing, and mentoring data science, data engineering, and analytics teams in a high scale technology company
- Preferred Qualifications:
- 15+ years’ experience in algorithmic engineering, data science, or machine learning
- 7+ years of experience in managing, and mentoring data science, data engineering, and analytics teams in a high scale technology company
- Deep technical background with a MS or PhD in mathematics, statistics, computer science or a related field
